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Book part
Publication date: 21 November 2014

Yixiao Sun

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual…

Abstract

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.

Book part
Publication date: 21 November 2014

Abstract

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

Content available
Book part
Publication date: 21 November 2014

Abstract

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

Article
Publication date: 8 February 2018

Guang Song, Luoyi Sun and Yixiao Wang

The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors…

Abstract

Purpose

The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors and the related significant drivers that support network designers in selecting the appropriate strategic supply chain configuration or checking the coherence of an existing supply chain structure in four industry sectors.

Design/methodology/approach

The decision-making model is developed based on an empirical study that integrates multiple case studies and statistical analyses. In total, 113 best-in-class manufacturing firms in four sectors are studied to investigate their strategic supply chain configurations and the information of identified affecting drivers. The factor analysis and regression analysis are conducted to classify the drivers into five factor groups, and to identify the significant drivers used to develop the decision-making model.

Findings

The findings of this research are three-pronged. First, 12 significant drivers related to 5 factor groups affecting strategic supply chain network design (SCND) are identified. Second, a decision-making model is developed to support users in strategic SCND. Last, the main characteristics of various strategic supply chain configurations are summarized in four industry sectors.

Research limitations/implications

The authors identified valuable insights for both academics and practitioners based on the identified significant affecting drivers and the developed decision-making model. In addition, this study also proposes two potential research lines on the study of additional contextual affecting factors and decision issues in strategic SCND.

Originality/value

This study could be the first attempt to use an empirically based method to develop a decision-making model aimed at supporting the preliminary design of a supply chain network. Therefore, the drawbacks of a pure qualitative conceptual model and optimization model are eliminated.

Details

Journal of Manufacturing Technology Management, vol. 29 no. 3
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 21 January 2022

ShunXiang Wei, Haibo Wu, Liang Liu, YiXiao Zhang, Jiang Chen and Quanfeng Li

To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern…

Abstract

Purpose

To achieve stable gait planning and enhance the motion performance of quadruped robot, this paper aims to propose a motion control strategy based on central pattern generator (CPG) and back-propagation neural network (BPNN).

Design/methodology/approach

First, the Kuramoto phase oscillator is used to construct the CPG network model, and a piecewise continuous phase difference matrix is designed to optimize the duty cycle of walk gait, so as to realize the gait planning and smooth switching. Second, the mapper between CPG output and joint drive is established based on BP neural network, so that the quadruped robot based on CPG control has better foot trajectory to enhance the motion performance. Finally, to obtain better mapping effect, an evaluation function is resigned to evaluate the proximity between the actual foot trajectory and the ideal foot trajectory. Genetic algorithm and particle swarm optimization are used to optimize the initial weights and thresholds of BPNN to obtain more accurate foot trajectory.

Findings

The method provides a solution for the smooth gait switching and foot trajectory of the robot. The quintic polynomial trajectory is selected to testify the validity and practicability of the method through simulation and prototype experiment.

Originality/value

The paper solved the incorrect duty cycle under the walk gait of CPG network constructed by Kuramoto phase oscillator, and made the robot have a better foot trajectory by mapper to enhance its motion performance.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

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